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Unitary Long-Time Evolution with Quantum Renormalization Groups and Artificial Neural Networks

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Burau,  Heiko
Max Planck Institute for the Physics of Complex Systems, Max Planck Society;

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Heyl,  Markus
Max Planck Institute for the Physics of Complex Systems, Max Planck Society;

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2009.04473.pdf
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Citation

Burau, H., & Heyl, M. (2021). Unitary Long-Time Evolution with Quantum Renormalization Groups and Artificial Neural Networks. Physical Review Letters, 127(5): 050601. doi:10.1103/PhysRevLett.127.050601.


Cite as: https://hdl.handle.net/21.11116/0000-0009-2925-0
Abstract
In this work, we combine quantum renormalization group approaches with deep artificial neural networks for the description of the real-time evolution in strongly disordered quantum matter. We find that this allows us to accurately compute the long-time coherent dynamics of large many-body localized systems in nonperturbative regimes including the effects of many-body resonances. Concretely, we use this approach to describe the spatiotemporal buildup of many-body localized spin-glass order in random Ising chains. We observe a fundamental difference to a noninteracting Anderson insulating Ising chain, where the order only develops over a finite spatial range. We further apply the approach to strongly disordered twodimensional Ising models, highlighting that our method can be used also for the description of the real-time dynamics of nonergodic quantum matter in a general context.